python-constraint | Constraint Solving Problem resolver for Python

 by   python-constraint Python Version: Current License: BSD-2-Clause

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Constraint Solving Problem resolver for Python
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            python-constraint Examples and Code Snippets

            solve equalities and inequalities with multiple variables in python
            Pythondot img1Lines of Code : 18dot img1License : Strong Copyleft (CC BY-SA 4.0)
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            import constraint
            
            problem = constraint.Problem()
            
            problem.addVariable('x', range(2))
            problem.addVariable('y', [1])
            
            def our_constraint(x, y):
                if 2*x + 4*y == 6:
                    return True
            
            problem.addConstraint(our_constraint, ['x','y'])
            
            so
            python root finding in integers
            Pythondot img2Lines of Code : 10dot img2License : Strong Copyleft (CC BY-SA 4.0)
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            # https://pypi.org/project/python-constraint/
            from constraint import *
            
            problem = Problem()
            problem.addVariables(["a","b"],range(1,100000))
            problem.addConstraint(ExactSumConstraint(5,[4,1]))
            problem.getSolutions()
            
            Python constraint adding variable with fixed value
            Pythondot img3Lines of Code : 5dot img3License : Strong Copyleft (CC BY-SA 4.0)
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            problem.addVariable(variables[15],[4])
            problem.addVariable(variables[12], [1])
            new_variables = variables[11:] + variables[13:14] + variables[:16]
            problem.addVariables(new_variables,domain)
            
            Given a list of numbers, find all matrices such that each column and row sum up to 264
            Pythondot img4Lines of Code : 50dot img4License : Strong Copyleft (CC BY-SA 4.0)
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            numbers = [11, 16, 18, 19, 61, 66, 68, 69, 81, 86, 88, 89, 91, 96, 98, 99]
            target = 264
            
            from constraint import *
            
            problem = Problem()
            problem.addVariables(range(16), numbers)
            
            for i in range(4):
                # column i
                v = [ i + 4*j for j in r
            Constrained optimization in python where one variable depends on another variable
            Pythondot img5Lines of Code : 68dot img5License : Strong Copyleft (CC BY-SA 4.0)
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            import kiwisolver
            
            x1 = kiwisolver.Variable('x1')
            x2 = kiwisolver.Variable('x2')
            x3 = kiwisolver.Variable('x3')
            x4 = kiwisolver.Variable('x4')
            
            constraints = [1995 <= 2*x1 + 4*x2 + 3*x3 + x4,
                           2*x1 + 4*x2 + 3*x3 + x4 <=
            python-constraint add dynamic constraint
            Pythondot img6Lines of Code : 24dot img6License : Strong Copyleft (CC BY-SA 4.0)
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            flight_names = ['MI428', 'UL867', 'QR664', 'TK730', 'UL303']
            flight_times = ['T-' + name for name in flight_names]
            bays_list = ['A1', 'A2', 'B1', 'B2', 'C1']
            
            times = range(20)   # or how many times you have
            
            problem.addVariables(flight_na
            python Constraints - constraining the amount
            Pythondot img7Lines of Code : 19dot img7License : Strong Copyleft (CC BY-SA 4.0)
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            from constraint import *
            
            D = 7 # number of devices
            L = 3 # number of locations
            
            maxdev = [3,4,2]
            allowed = [[1,3,7],[1,3,4,5,6,7],[2,4,5,6]]
            
            problem = Problem()
            problem.addVariables(["x_L%d_d%d" %(loc+1,d+1) for loc in range(L) for d in 
            Python constraint inverse
            Pythondot img8Lines of Code : 14dot img8License : Strong Copyleft (CC BY-SA 4.0)
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            from constraint import Problem, ExactSumConstraint
            problem = Problem()
            MaximumSum = 10
            MaxMultiplicationSum = 40
            Variables = ("a", "b", "c", "d")
            realKeys = {'a': 2, 'b': 3, 'c': 4, 'd': 5}
            for Variable in Variables:
                problem.addVariabl
            Odoo - Give a warning when editing some field with empty value
            Pythondot img9Lines of Code : 11dot img9License : Strong Copyleft (CC BY-SA 4.0)
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            class product_template(models.Model):
                _inherit = 'product.template'
            
                @api.multi
                @api.constrains('seller_ids')
                def onchange_seller(self):
                    for record in self :
                        if not record.seller_ids :
                            ra
            Python element-wise sum and consecutive times constraint
            Pythondot img10Lines of Code : 18dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            from itertools import groupby
            
            a = [10, 11, 12, 13, 14]
            b = [15, 16, 17, 18, 19]
            c = [20, 21, 22, 23, 24]
            
            data = [a, b, c]
            
            def keyfunc(t):
                return sum(t) > 50
            
            for k, g in groupby(zip(*data), keyfunc):
                if k:
                    g = list(g)

            Community Discussions

            QUESTION

            Constrained optimization in python where one variable depends on another variable
            Asked 2019-May-09 at 14:54

            I have a problem where I have 4 variables x1, x2, x3 and x4. I need to find the values for x1, x2, x3, x4 with the following conditions:

            ...

            ANSWER

            Answered 2019-May-09 at 14:54

            Your problem is, in fact, linear, and so it's ideally suited to a linear programming approach. However, you are giving it to the solver with no clues as to the linearity of the problem, so it's bound to find that tricky: it pretty much has to try every possibility which is going to take a long time. It might be possible to rewrite your constraints into different forms for the python-constraint solver (it has, for example, a MaxSumConstraint constraint form) which might work better but ideally I think you should be using a solver specialised for linear problems.

            There is a solver called kiwisolver which will do what you want. Here's your example converted for that library:

            Source https://stackoverflow.com/questions/56042803

            QUESTION

            python Constraints - constraining the amount
            Asked 2018-Apr-06 at 13:09

            I have a constraint problem that I'm trying to solve with python-constraint

            So let's say I have 3 locations: loc1,...loc3

            Also, I have 7 devices: device1,...device7

            Max amount of devices in each location: loc1:3, loc2:4, loc3:2 (for example maximum of 3 devices in loc1 and so on...)

            And some constraints about the locations and the devices:

            loc1: device1, device3, device7,

            loc2: device1, device3, device4, device5, device6, device7

            loc3: device2, device4, device5, device6

            (meaning for example only device1, device3 and device7 can be in loc1.)

            I'm trying to get a set of possible options for devices in locations.

            ...

            ANSWER

            Answered 2018-Apr-06 at 13:09

            This is simple assignment-like model:

            So we have a binary variable indicating if device d is assigned to location L. The linear constraints are just:

            • assign each device to one location
            • each location has a maximum number of devices
            • make sure to use only allowed assignments (modeled above by allowed(L,d))

            This problem can be handled by any constraint solver.

            Enumerating all possible solutions is a bit dangerous. For large instances there are just way too many. Even for this small problem we already have 25 solutions:

            For large problems this number will be astronomically large.

            Using the Python constraint package this can look like:

            Source https://stackoverflow.com/questions/49655875

            QUESTION

            Python element-wise sum and consecutive times constraint
            Asked 2017-Aug-10 at 20:18

            I have data like this.

            ...

            ANSWER

            Answered 2017-Aug-10 at 20:18

            I suggest you investigate itertools.groupby. Eg, here's some code that will find & count runs of consecutive columns that sum to >50.

            Source https://stackoverflow.com/questions/45621498

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

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